Error Rates of Non-Bayes Classification Rules and the Robustness of Fisher's Linear Discriminant Function
研究了非贝叶斯分类规则的错误率，并评估了Fisher线性判别函数在偏离假设时的稳健性，对统计分类方法的选择有参考价值。
Error rates of non-Bayes classification rules and the robustness of Fisher's linear discriminant function Get access TERENCE J. O'NEILL TERENCE J. O'NEILL Department of Statistics, Faculty of Economics and Commerce, Australian National UniversityGPO Box 4, Canberra ACT 2601, Australia Search for other works by this author on: Oxford Academic Google Scholar Biometrika, Volume 79, Issue 1, March 1992, Pages 177–184, https://doi.org/10.1093/biomet/79.1.177 Published: 01 March 1992